Backpropagation: Chain Rule to the Third Last Layer
I finally solved it out but it's long, it's not only chain rule, it includes quotient rule too. And, this is only the third last layer, once a DNN has more layers then it's more complex.

$\dfrac{dLoss}{dW_1} = \dfrac{d}{dW_1}(Out-Y) = \dfrac{d}{dW_1}Out = \dfrac{d}{dW_1}(H_4W_{13} + H_5W_{14}) \\= \dfrac{d}{dW_1}H_4W_{13} + \dfrac{d}{dW_1}H_5W_{14} \\= W_{13} \times \dfrac{d}{dW_1}H_4 + W_{14} \times \dfrac{d}{dW_1}H_5 \\= W_{13} \times \dfrac{d}{dW_1}(H_1W_7 + H_2W_8 + H_3W_9) + W_{14} \times \dfrac{d}{dW_1}(H_1W_{10} + H_2W_{11} + H_3W_{12}) \\= W_{13} \times \dfrac{d}{dW_1}H_1W_7 + W_{14} \times \dfrac{d}{dW_1}H_1W_{10} \\= W_{13}W_7 \times \dfrac{d}{dW_1}H_1 + W_{14}W_{10} \times \dfrac{d}{dW_1}H_1 \\= (W_{13}W_7 + W_{14}W_{10}) \times \dfrac{d}{dW_1}(X_1W_1 + X_2W_2) \\= (W_{13}W_7 + W_{14}W_{10}) \times X_1$